1. Field of the Invention
This invention generally relates to methods for controlling one or more parameters of a flow cytometer type measurement system. Certain embodiments relate to methods that include altering one or more parameters of a flow cytometer type measurement system in real time based on monitoring of the parameter(s).
2. Description of the Related Art
The following descriptions and examples are not admitted to be prior art by virtue of their inclusion within this section.
Generally, flow cytometers provide measurements of fluorescence intensity of laser excited polystyrene beads or cells as they pass linearly through a flow chamber. However, flow cytometers can also be used to provide measurements of one or more properties of other particles. Some systems are configured to perform measurements of the level of light scattered by particles at 90° or 180° to the excitation source, two or more measurements of fluorescence used to determine classification, which is the particle “identity,” and additional fluorescence measurements known as “reporters,” typically used to quantify chemical reactions of interest. Each of the fluorescent measurements is made at different wavelengths.
As the measurement capability of flow cytometer type measurement instruments has improved, the applications in which flow cytometers can provide useful measurements has increased drastically. For example, flow cytometers have become increasingly useful in providing data for applications such as biological assays (e.g., displacement or competition assays, non-competition assays, enzyme assays), nucleic acid analysis, and combinatorial chemistry. In particular, the popularity of flow cytometer measurements has dramatically increased due to the speed with which assays can be performed particularly in comparison to other assay methods (e.g., conventional enzyme linked immunosorbent assay “ELISA” format).
Under normal circumstances, calibration of flow cytometers occurs as one or more preliminary steps in preparing instruments for proper use and measurement to ensure accurate and reliable assay results. In addition, unless the fluorescence channels of each flow cytometer are calibrated to read the same, there is no assurance as to the source of variation among samples. It is likely that one instrument will give different readings on the same sample on different days if robust and complete calibration methods are not employed. Similarly, if there is no assurance that any two instruments will provide the same results even if properly set up, although flow cytometry may provide a better measure of identifying and distinguishing between cells in a sample, its use as a clinical instrument may be diminished.
Accordingly, many different methods for calibrating a flow cytometer have been developed. Initially, significant work was done to develop calibration methods that reduced the level of involvement of the operator in calibration to increase the accuracy of the calibration. This work led, in large part, to the automation of many steps of the calibration of flow cytometers. In addition, significant work was done to improve the accuracy of the calibration in other ways. For example, this work has led to advancement in calibrations such as using calibration standards that have uniform and constant properties. In particular, since the properties of biological samples can change over time, biological calibration standards for flow cytometers have generally been replaced with synthetic calibration standards (e.g., polymeric microspheres or particles) that have more stable properties. In addition, typically the calibration microspheres have properties (e.g., size, volume, surface characteristics, granularity properties, refractive index, fluorescence, etc.) that are substantially similar (i.e., as close as possible) to the properties of the test microspheres. Such calibration microspheres were believed to increase the accuracy of the flow cytometer by performing calibration at values that are as close as possible to the values that were expected during testing.
Attempts to improve the calibration of flow cytometers have also led to increasing the number of parameters of the flow cytometer that are accounted for by calibration. For example, the laser excitation, detectors, and electronics of flow cytometer measurement systems vary over time, which affects the final measurement. Therefore, these, and sometimes other, parameters of flow cytometers are typically accounted for by calibration methods.
Other parameters, which are more difficult to control, also affect the measurements of a flow cytometer. One such parameter is sample velocity. One example of a method for measuring sample velocity is illustrated in U.S. Pat. No. 6,532,061 Ortyn et al., which is incorporated by reference as if fully set forth herein. In this method, objects are entrained in a flow of fluid, which is caused to flow through the sensitive or measurement volume. In each of these embodiments, optical gratings having a substantially uniform pitch are employed to modulate light received from the moving objects. The modulated light is converted into an electrical signal, which is digitized and then processed using a Fast Fourier Transform (FFT) to determine the velocity of the object. There are, however, several disadvantages to the methods and systems described by Ortyn et al. for measuring sample velocity. For example, the methods require fairly complex optical gratings and software. In addition, due to the precision required for the optical gratings and the complexity of manufacturing, the optical gratings may be fairly expensive. Furthermore, the sample velocity measurements may be somewhat inaccurate due, for example, to the optical distortion of the detected light by the moving objects.
However, the most significant error contribution in flow cytometer measurements is generally caused by temperature variance. In addition, it has been found that the effect of temperature variance on the measurements performed by a flow cytometer is not adequately accounted for by the presently available calibration methods. For example, the methods and systems described by Ortyn et al., although attempting to correct for a number of parameters, do not take into account temperature variations and how they affect the measurements of a flow cytometer. Therefore, although many different calibration methods are available, additional improvements to each of these methods can be made by more accurately accounting for temperature variations during different flow cytometer measurements or during individual flow cytometer measurements.
Accordingly, it may be advantageous to develop methods for controlling at least the major error contributing components of flow cytometer measurement systems, which could be combined to produce a real time calibration scheme.